Bayesian policy selection using active inference. - Ozan Çatal; Johannes Nauta; Tim Verbelen; Pieter Simoens; Bart Dhoedt (CoRR, 2019)

Learning Perception and Planning With Deep Active Inference. - Ozan Çatal; Tim Verbelen; Johannes Nauta; Cedric De Boom; Bart Dhoedt (ICASSP, 2020)

Anomaly Detection for Autonomous Guided Vehicles using Bayesian Surprise. - Ozan Çatal; Sam Leroux; Cedric De Boom; Tim Verbelen; Bart Dhoedt (IROS, 2020)

You Only Look as Much as You Have To - Using the Free Energy Principle for Active Vision. - Toon Van de Maele; Tim Verbelen; Ozan Çatal; Cedric De Boom; Bart Dhoedt (IWAI, 2020)

Sleep: Model Reduction in Deep Active Inference. - Samuel T. Wauthier; Ozan Çatal; Cedric De Boom; Tim Verbelen; Bart Dhoedt (IWAI, 2020)

Learning to Catch Piglets in Flight. - Ozan Çatal; Lawrence De Mol; Tim Verbelen; Bart Dhoedt (CoRR, 2020)

Deep Active Inference for Autonomous Robot Navigation. - Ozan Çatal; Samuel Wauthier; Tim Verbelen; Cedric De Boom; Bart Dhoedt (CoRR, 2020)

Learning Generative State Space Models for Active Inference. - Ozan Çatal; Samuel Wauthier; Cedric De Boom; Tim Verbelen; Bart Dhoedt (Frontiers Comput. Neurosci., 2020)

LatentSLAM: unsupervised multi-sensor representation learning for localization and mapping. - Ozan Çatal; Wouter Jansen; Tim Verbelen; Bart Dhoedt; Jan Steckel (ICRA, 2021)

Disentangling What and Where for 3D Object-Centric Representations Through Active Inference. - Toon Van de Maele; Tim Verbelen; Ozan Çatal; Bart Dhoedt (PKDD/ECML Workshops (1), 2021)

Self-Supervised Exploration via Latent Bayesian Surprise. - Pietro Mazzaglia; Ozan Çatal; Tim Verbelen; Bart Dhoedt (CoRR, 2021)

A learning gap between neuroscience and reinforcement learning. - Samuel T. Wauthier; Pietro Mazzaglia; Ozan Çatal; Cedric De Boom; Tim Verbelen; Bart Dhoedt (CoRR, 2021)

Towards bio-inspired unsupervised representation learning for indoor aerial navigation. - Ni Wang; Ozan Çatal; Tim Verbelen; Matthias Hartmann; Bart Dhoedt (CoRR, 2021)

Active Vision for Robot Manipulators Using the Free Energy Principle. - Toon Van de Maele; Tim Verbelen; Ozan Çatal; Cedric De Boom; Bart Dhoedt (Frontiers Neurorobotics, 2021)

Robot navigation as hierarchical active inference. - Ozan Çatal; Tim Verbelen; Toon Van de Maele; Bart Dhoedt; Adam Safron (Neural Networks, 2021)

Curiosity-Driven Exploration via Latent Bayesian Surprise. - Pietro Mazzaglia; Ozan Çatal; Tim Verbelen; Bart Dhoedt (AAAI, 2022)

Bio-inspired monocular drone SLAM. - Ozan Çatal; Tim Verbelen; Ni Wang; Matthias Hartmann; Bart Dhoedt (DroneSE/RAPIDO@HiPEAC, 2022)

The Free Energy Principle for Perception and Action: A Deep Learning Perspective. - Pietro Mazzaglia; Tim Verbelen; Ozan Çatal; Bart Dhoedt (Entropy, 2022)

Embodied Object Representation Learning and Recognition. - Toon Van de Maele; Tim Verbelen; Ozan Çatal; Bart Dhoedt (Frontiers Neurorobotics, 2022)

Model Reduction Through Progressive Latent Space Pruning in Deep Active Inference. - Samuel T. Wauthier; Cedric De Boom; Ozan Çatal; Tim Verbelen; Bart Dhoedt (Frontiers Neurorobotics, 2022)

FMCW Radar Sensing for Indoor Drones Using Learned Representations. - Ali Safa; Tim Verbelen; Ozan Çatal; Toon Van de Maele; Matthias Hartmann; Bart Dhoedt; André Bourdoux (CoRR, 2023)

Belief Sharing: A Blessing or a Curse. - Ozan Çatal; Toon Van de Maele; Riddhi J. Pitliya; Mahault Albarracin; Candice Pattisapu; Tim Verbelen (IWAI, 2024)

Variational Bayes Gaussian Splatting. - Toon Van de Maele; Ozan Çatal; Alexander Tschantz; Christopher L. Buckley; Tim Verbelen (CoRR, 2024)

AXIOM: Learning to Play Games in Minutes with Expanding Object-Centric Models. - Conor Heins; Toon Van de Maele; Alexander Tschantz; Hampus Linander; Dimitrije Markovic; Tommaso Salvatori; Corrado Pezzato; Ozan Çatal; Ran Wei; Magnus T. Koudahl; Marco Perin; Karl J. Friston; et al. (CoRR, 2025)

Mobile Manipulation with Active Inference for Long-Horizon Rearrangement Tasks. - Corrado Pezzato; Ozan Çatal; Toon Van de Maele; Riddhi J. Pitliya; Tim Verbelen (CoRR, 2025)